Inspired by Anthropic CEO Dario Amodei's essay Machines of Loving Grace, this hackathon asks one question: how can AI help people flourish?

We're not looking for solutions to hypothetical problems. We want tools built for specific people facing real challenges. We want to see your thinking as much as your code.

There are 4 tracks to compete in:

1. Biology & Physical Health. Healthcare is expensive, inaccessible, and confusing. Build something that helps people access care, understand their health, or navigate complex medical systems.

Examples: 

• Diagnostic aids for underserved clinics

• Patient education platforms 

• Medication adherence tools

• Symptom assessment and triage 

• Health literacy for treatment decisions 

• Accessibility tools for people with disabilities navigating healthcare

Track-specific ethical considerations:

• Medical accuracy - when should this hand off to a real professional?

• Privacy of deeply sensitive health data

• Bias in medical AI across different populations

• Transparency about limitations and when professional care is needed

2. Neuroscience & Mental Health. There aren't enough therapists. Stigma keeps people from seeking help. Geography and insurance gate good care. Build tools that expand access to mental health support and understanding.

Examples: 

• Always-available therapeutic support using evidence-based approaches  

• Mental health literacy and psychoeducation 

• Tools for recognizing when you need professional help 

• Stress and burnout prevention 

• Peer support facilitation 

• Accessibility tools for neurodivergent individuals

Track-specific ethical considerations:

• Crisis situations - when does someone need immediate human intervention?

• Privacy and stigma around mental health data

• Avoiding harm through bad psychological advice

• Cultural competence in mental health approaches

• Transparency about what AI therapy can and can't do

• Not replacing human connection when it's needed

3. Economic Empowerment & Education. Talent is everywhere. Opportunity isn't. Remove barriers to learning, skill-building, and economic advancement for people currently locked out.

Examples: 

• Adaptive tutoring  

• Career transition guidance  

• Financial literacy for underserved communities 

• Job interview prep 

• Small business/nonprofit support 

• Scholarship matching 

• Practical language learning

Track-specific ethical considerations:

• Who gets excluded by your design (tech requirements, literacy levels, language)?

• Impact of bad advice when guiding careers or education

• Empowering informed choices vs. making choices for people

• Cultural assumptions about what "success" means

4. Creative Flourishing. As AI handles routine work, questions of human purpose grow urgent. Amplify creativity. Preserve culture. Help people find meaning.

Every team must answer three questions:

• Who are you building this for, and why do they need it?

• What could go wrong, and what would you do about it?

• How does this help people rather than make decisions for them?

Examples: 

• Community storytelling platforms

• Music/art education with real-time feedback  

• Writing development tools 

• Language preservation 

• Skill development for crafts/instruments 

• Intergenerational knowledge exchange 

• Purpose exploration guides

Track-specific ethical considerations:

• Keeping humans as creators using tools (not AI as creator with human prompter)

• Enhancing vs. short-cutting the creative process in ways that diminish it

• Cultural appropriation vs. respectful celebration

• Homogenization of creative voices

• Creating vs. destroying value for creative workers

Schedule

• Real-World Impact
  Does this solve a real problem? Who benefits and how? Could it scale?
• Technical Execution
  Does it work? Is it well-built? Does it use AI effectively?
• Ethical Alignment
  Does it center human dignity? Does it address potential harms? Does it expand access equitably?
• Presentation Quality
  Can you clearly explain what you built and why it matters?